brownian-diffuser

Forward integrate torch neural networks

Similar to torchsde.sdeint or torchdiffeq.odeint but for vanilla neural networks as implemented by TorchNets

BrownianDiffuser

from brownian_diffuser import BrownianDiffuser

diffuser = BrownianDiffuser()

from torch_nets import TorchNet
import torch

net = TorchNet(50, 50, [400, 400])
X0 = torch.randn([200, 50])
t = torch.Tensor([2, 4, 6])

X_pred = diffuser(net, X0, t, n_steps=40, stdev=0.5, max_steps=None, return_all=False)
X_pred.shape

torch.Size([3, 200, 50])

BrownianMotion

from brownian_diffuser import BrownianMotion

X_state = torch.randn([400, 50])

BM = BrownianMotion(X_state, stdev=0.5, n_steps=40)
Z = BM()
Z.shape

torch.Size([40, 400, 50])

pip install brownian-diffuser

mvinyard/brownian-diffuser